Abstract

The Exploration of Metabolic Biomarkers blood Lipidomics and Proteomics for diagnosing Alzheimer's disease

Author(s): J Tingyu Zhao1, Ting Wang2, Zihui Sun1,3, Lixing Liu1, Haiyan Wu1, Li Zhang1, Li Ma1, Xueling He1, Yuyao Yuan4, Fan Mei4, Yuxin Yin4† and Shouzi Zhang1†

Introduction: Alzheimer’s Disease (AD) is the most common neurodegenerative disorder; however, its underlying mechanisms remain incompletely understood, posing challenges for early diagnosis. This study aimed to explore potential metabolic biomarkers for AD in blood. Methods: We recruited 82 participants, including 47 AD patients (age: 80.2 ± 0.9 years) and 35 healthy controls (age: 77.6 ± 1.7 years). Blood samples were collected and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography coupled with Q-Exactive HF MS. Data processing was performed using MS-DIAL, Skyline, and MaxQuant software. Metabolic pathway analysis was conducted with MetaboAnalyst, and enrichment analysis of differential metabolites was based on the KEGG database. Results: Significant alterations were observed in amino acid metabolic pathways, including lysine degradation, pyruvate metabolism, glycine, serine and threonine metabolism, linolenic acid metabolism, and arginine and proline metabolism. Lipidomics analysis revealed seven lipids that were significantly elevated in the AD group: Cer 40:9;O3, DG 25:0, DG 46:7, NAE 16:1, PC 20:1/22:5, PC O-35:5, and TG 45:7. Notably, Receiver Operating Characteristic (ROC) curve analysis showed that the Area Under the Curve (AUC) values for these seven lipids all exceeded 0.8. Discussion: This comprehensive multi-omics approach effectively identified dysregulated plasma molecules in AD patients, suggesting that specific blood lipids may serve as potential biomarkers for AD diagnosis.